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Econometrics 2013, 1(2), 141-156; doi:10.3390/econometrics1020141

Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging

Graduate School of Economics, Kyoto University, Yoshida-Hommachi, Sakyo-ku, Kyoto, 6068501,Japan
Received: 13 May 2013 / Revised: 26 June 2013 / Accepted: 27 June 2013 / Published: 3 July 2013
(This article belongs to the Special Issue Econometric Model Selection)
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Abstract

This paper develops model selection and averaging methods for moment restriction models. We first propose a focused information criterion based on the generalized empirical likelihood estimator. We address the issue of selecting an optimal model, rather than a correct model, for estimating a specific parameter of interest. Then, this study investigates a generalized empirical likelihood-based model averaging estimator that minimizes the asymptotic mean squared error. A simulation study suggests that our averaging estimator can be a useful alternative to existing post-selection estimators.
Keywords: model selection; model averaging; focused information criterion; generalized empirical likelihood model selection; model averaging; focused information criterion; generalized empirical likelihood
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Sueishi, N. Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging. Econometrics 2013, 1, 141-156.

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